Matching Methods in Practice: Three Examples

There is a large theoretical literature on methods for estimating causal effects under unconfoundedness, exogeneity, or selection--on--observables type assumptions using matching or propensity score methods. Much of this literature is highly technical and has not made inroads into empirical practice where many researchers continue to use simple methods such as ordinary least squares regression even in settings where those methods do not have attractive properties. In this paper I discuss some of the lessons for practice from the theoretical literature, and provide detailed recommendations on what to do. I illustrate the recommendations with three detailed applications.

If you usually get free papers at work/university but do not at home,
you can either
connect to your work VPN or proxy (if any) or elect to have a link to the paper
emailed to your work email address below. The email address must be
connected to a
subscribing college, university, or other subscribing institution.
Gmail and other free email addresses will not have access.